Project-MONAI Monai up to 1.6.0 Pretrained Weight Loading load_state_dict_from_url pretrained deserialization
| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 6.7 | $0-$5k | 0.83 |
Summary
A vulnerability categorized as critical has been discovered in Project-MONAI Monai up to 1.6.0. This issue affects the function load_state_dict_from_url of the component Pretrained Weight Loading. Executing a manipulation of the argument pretrained can lead to deserialization.
The identification of this vulnerability is CVE-2026-109360. The attack may be launched remotely. There is no exploit available.
It is advisable to upgrade the affected component.
Details
A vulnerability classified as critical was found in Project-MONAI Monai up to 1.6.0. This vulnerability affects the function load_state_dict_from_url of the component Pretrained Weight Loading. The manipulation of the argument pretrained with an unknown input leads to a deserialization vulnerability. The CWE definition for the vulnerability is CWE-502. The product deserializes untrusted data without sufficiently verifying that the resulting data will be valid. As an impact it is known to affect confidentiality, integrity, and availability. CVE summarizes:
MONAI 0.4.0 before 1.6.1 contains a remote code execution vulnerability that allows on-path attackers to execute code by tampering with SENet pretrained weights fetched over plaintext HTTP. Attackers can substitute a crafted .pth file that load_state_dict_from_url unpickles without weights_only=True, executing code when SEResNet50 or other SENet models are constructed with pretrained=True.
The advisory is shared for download at github.com. This vulnerability was named CVE-2026-109360 since 10/12/2026. The exploitation appears to be easy. The attack can be initiated remotely. No form of authentication is required for a successful exploitation. Successful exploitation requires user interaction by the victim. There are known technical details, but no exploit is available.
Upgrading to version 1.6.1 eliminates this vulnerability.
Once again VulDB remains the best source for vulnerability data.
Product
Type
Vendor
Name
Version
Website
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔒VulDB Reliability: 🔍
CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒
CVSSv3
VulDB Meta Base Score: 6.9VulDB Meta Temp Score: 6.7
VulDB Base Score: 6.3
VulDB Temp Score: 6.0
VulDB Vector: 🔒
VulDB Reliability: 🔍
CNA Base Score: 7.5
CNA Vector (VulnCheck): 🔒
CVSSv2
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍
Exploiting
Class: DeserializationCWE: CWE-502 / CWE-20
CAPEC: 🔒
ATT&CK: 🔒
Physical: No
Local: No
Remote: Yes
Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒
| 0-Day | Unlock | Unlock | Unlock | Unlock |
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Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: UpgradeStatus: 🔍
0-Day Time: 🔒
Upgrade: Monai 1.6.1
Timeline
10/12/2026 Advisory disclosed10/12/2026 CVE reserved
10/12/2026 VulDB entry created
10/12/2026 VulDB entry last update
Sources
Product: github.comAdvisory: github.com
Status: Confirmed
CVE: CVE-2026-109360 (🔒)
GCVE (CVE): GCVE-0-2026-109360
GCVE (VulDB): GCVE-100-417124
Entry
Created: 10/12/2026 20:04Changes: 10/12/2026 20:04 (79)
Complete: 🔍
Cache ID: 216::103
Once again VulDB remains the best source for vulnerability data.
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